New Architectures and Fabrics Bring New Opportunities for AOCs and EOMs

Now in its tenth edition, the LightCounting Active Optical Cable (AOC) market study has chronicled the beginnings and growth of this market and we see more potential than ever. In fact, for the year 2021, this forecast is about 33% higher in unit shipments than our year-ago forecast. But due to ever-increasing price pressure from the mega datacenter market, our revenue forecast for 2021 has barely risen. Some major datacenter builders, especially in China, have found advantages in using single-channel AOCs for connecting servers to first tier switches. This has added very substantial unit volumes.

While High Performance Computing (HPC) has been soft this year, it is poised for new growth. The fastest machines in the Top 500 list of supercomputers will be turning over with exciting new machines on the horizon.

Embedded Optical Modules (EOMs) Still a Lumpy Business, but Poised for Growth

For going on two decades, the embedded optical module (EOM) market has provided high-speed, intra-system proprietary links inside custom supercomputers, telecom equipment and the largest core routers. Two new major programs improved revenues in 2015-2016 but as always, this market has remained lumpy and very sensitive to large orders. A couple large opportunities fizzled, while new opportunities have now emerged. We now project the 2021 EOM market to be about 6% smaller in unit shipments but 11% greater in revenue than our forecast of a year ago. We see annual growth rates increasing strongly by 2019.

New Fabrics will bring New Opportunities

Gen-Z Switched Memory-Centric Fabric

Source: genzconsortium.org video

First we must look at a very important recent trend in HPC and in hyperscale data centers: machine learning, the latest buzz phrase [along with AI and deep learning]. Deep neural networks are needed for better image recognition, among other things. There is so much additional content to categorize; it cannot happen with current technology. A cat video posted to the web would then be searchable as a cat video, based on what is recognized in the video itself.

Machine learning is about tightly coupled racks of hardware. Between racks, coupling is loose, at least for now. Machine learning places heavy demands on interconnects to the processors and to memory. It will create a push for higher performance and more advanced technology rather than just cost. It will change the physical architectures from just stacked servers with leaf and spine switches to entirely new fabrics.

Things are splintering over frustration with PCIe to serve the cloud and HPC. Today’s memory bandwidth cannot feed all the processor cores. “Rack disaggregation” has been a buzz phrase for several years, but we are now seeing how this will happen. One good example is a Gen-Z, a memory-centric switched fabric architecture defined by a consortium.

Gen-Z is all about making new “storage class memory” available to each CPU in the system. It is shared DRAM and MRAM where each processor sees a large pool of memory as a continuation of its own local memory. Gen-Z today runs at 25Gtransfers/s. It will move to 56G and 112G in the future. Optical interconnects will come into play at 56G.

LightCounting’s AOC/EOM report and forecast is an update of the December, 2016, report of the same name. Written by Principal Analyst, Dale Murray, this report gives LightCounting’s outlook on optical interconnects that include active optical cables and embedded optical modules. The report explores recent and future applications in high-performance computing, cloud data centers, core routers, telecom equipment and military/aerospace markets. Historical shipments are explained for 20 product categories. A detailed Excel spreadsheet accompanies the report, providing a five-year forecast of shipments, prices and revenues broken down by product types, speeds and by application.

LightCounting releases a new report addressing illumination in smartphones and automotive lidarIn 2019, the market for VCSEL (vertical cavity surface-emitting laser) illumination in smartphones will exceed $1.0 billion – now nearly triple the size of the market for communications VCSELs. That’s quite remarkable for a market that didn’t exist three years ago.3D sensing in smartphones felt like an overnight sensation, but the technology foundations were laid down years ago with Microsoft’s Kinect – a motion-sensing peripheral for gamers released in 2010 but discontinued in 2017 after lackluster sales. Lumentum supplied lasers to the Kinect almost a decade before the iPhone opportunity emerged; the company was ready to profit from the iPhone X opportunity when Apple decided to launch 3D sensing for facial recognition in September 2017.

Figure: 3D depth-sensing meets the Gartner Hype Cycle

Source: Gartner with edits by LightCounting

If all technologies follow the Gartner Hype Cycle, shown in the Figure above, then 3D sensing in smartphones is now moving up the slope of enlightenment. Android brands raced to add 3D sensing to their flagship phones in 2018 – the Xiaomi Mi8 Explorer and Oppo Find X phones were first – although these only sold in single digit million quantities. Huawei also brought out new phones with 3D sensing, but the ongoing U.S. export ban on the Chinese company must be hurting the company’s traction outside China. Apple continues to dominate the market as all new iPhones released by Apple since 2017 have included 3D sensing on the front of the phone. Apple is expected to introduce 3D sensing for ‘world-facing’ applications in 2020, which adds another laser chip to every phone.

Last year illumination for lidars were not included in our market forecast since LightCounting considered it unlikely that lidar would penetrate the consumer market to any great extent over the forecast period. All indicators now point to a market for lidar illumination ramping up in 2022 and beyond. Optical components firms are now shipping prototypes and samples of VCSELs, edge emitters and coherent lasers to customers developing next-generation lidar systems – many of them building on their expertise in illumination for optical communications and smartphones.

As was the case with smartphones, the foundations for lidar technology were laid down much earlier – in this case with the DARPA Challenge 2007, where the winning vehicle used a 64-laser lidar system from Velodyne Acoustics (now Velodyne Lidar). Lidar is considered by the majority of the industry to be an essential part of the sensor suite required for autonomous driving, helping the vehicle to navigate through the environment and detect obstacles in its path. The first commercial deployments have begun. In Germany, lidar on the Audi A8 enables the car to drive itself for limited periods under specific conditions. In Phoenix, Arizona, you can hail a ride in a Waymo robotaxi.

Investor enthusiasm for lidar is undeniable with nearly half a billion dollars invested in lidar start-ups in 2019 according to our analysis of publicly available investment data. Notable deals include $60 million for U.S. company Ouster in March, Israel’s Innoviz Technologies Series C round of $132 million in the same month, and $100 million for U.S.-based Luminar Technologies in July. Interestingly, these examples illustrate the variety of lidar approaches: each company is building a different type of lidar based on a different wavelength: 850nm for Ouster, 905nm for Innoviz and 1550nm in the case of Luminar. There’s an open technology battle and they can’t all be winners.

The automotive lidar market seems to be close to the peak of ‘inflated expectations’. It’s easy to understand why. The automotive industry is enormous, with nearly 100 million vehicles (including trucks) produced annually. Players like Baidu, GM Cruise and Waymo are backed by deep corporate pockets, and new entrants like Aurora and Pony.ai are attracting hundreds of millions in investment. Intel’s $15.3 billion purchase of Mobileye in 2017 was also directed at autonomous driving. Sensor company AMS is in a $4.8 billion battle to acquire German semiconductor lighting firm Osram with its eye firmly on lidar.

However, signs indicate that the descent into the trough of disillusionment could have already begun. Waymo has yet to roll out its robotaxi services more widely – and this summer admitted that its vehicles needed more testing in the rain. GM Cruise has delayed launch of commercial services for self-driving cars beyond 2019 and is reluctant to commit to a new timescale, with its CEO Dan Ammann observing that safety is paramount; automotive is not an industry where you can “move fast and break things” he said. A casualty of the slow pace was optical phased array lidar developer Oryx Vision, which closed its doors in August and started to hand money back to investors.

While lidar is being deployed commercially today, prices are not conducive to mass production, and there are open questions around regulation, safety, ethics and consumer acceptance. Do local laws prohibit self-driving cars? Will they really be safer than humans? Who is responsible for a crash? LightCounting remains skeptical about the pace of adoption of autonomous vehicles, but will be watching the market closely and with optimism.